RT journal article
T1 Structuring Heterogeneous Urban Data: A Framework to Develop the Data Model for Energy Simulation of Cities
A1 Dabirian, Sanam
A1 Saad, Mostafa M.
A1 Hussain, Sadam
A1 Peyman, Sareh
A1 Rahim, Negarsadat
A1 Monsalvete Álvarez de Uribarri, María Del Pilar
A1 Yefi, Peter
A1 Eicker, U.
A2 Máquinas y Motores Térmicos
K1 Data modeling
K1 Urban energy modeling
K1 Data interoperability
K1 Digital twins
K1 Decarbonizing Cities
AB Globally, there is accelerating interest in cities and the analysis of their underlying systems to understand, project, and propose sustainable energy transformations. These urban areas represent a complex combination of heterogeneous data, which complicates the process of engineering modeling and predicting changes that could occur. Identifying the data sources related to the urban objects and their associated characteristics is essential. While some schemas are developed to collect, consolidate, and organize the required data, such as CityGML, to describe urban geometry semantically, they lack the capability to include different use cases and objectives to adequately parametrize simulation models. There is a lack of a well-structured framework for data modeling to efficiently organize the dispersed data needed for urban energy simulation. This article proposes a framework to develop urban data models connecting with urban energy modeling tools for energy assessments in the city context. The paper’s main contribution is presenting a novel implementation methodology for processing, modeling, capturing the results, and populating other existing standard data formats. The data model represents a key element in a novel urban simulation platform and aims at real-time capturing, storing, and investigating the various aspects of city-scale behavior and performance.
PB Elsevier
SN 0378-7788
YR 2023
FD 2023
LK http://hdl.handle.net/10498/36985
UL http://hdl.handle.net/10498/36985
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 22-sep-2026